565 citations · 3.2k across the 41 of their papers we have counts for
43 papers
Exact Selective Inference with Randomization
Snigdha Panigrahi, Kevin Fry, Jonathan Taylor
We introduce a pivot for exact selective inference with randomization. Not only does our pivot lead to exact inference in Gaussian regression models, but it is also available in cl…
Black-box Selective Inference via Bootstrapping
Sifan Liu, Jelena Markovic-Voronov, Jonathan Taylor
Conditional selective inference requires an exact characterization of the selection event, which is often unavailable except for a few examples like the lasso. This work addresses…
Inferring Treatment Effects After Testing Instrument Strength in Linear Models
Nan Bi, Hyunseung Kang, Jonathan Taylor
A common practice in IV studies is to check for instrument strength, i.e. its association to the treatment, with an F-test from regression. If the F-statistic is above some thresho…
Inference After Selecting Plausibly Valid Instruments with Application to Mendelian Randomization
Nan Bi, Hyunseung Kang, Jonathan Taylor
Mendelian randomization (MR) is a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome by using genetic instruments. These instruments are oft…
Approximate selective inference via maximum likelihood
Snigdha Panigrahi, Jonathan Taylor
Several strategies have been developed recently to ensure valid inference after model selection; some of these are easy to compute, while others fare better in terms of inferential…
Inference after black box selection
Jelena Markovic, Jonathan Taylor, Jeremy Taylor
We consider the problem of inference for parameters selected to report only after some algorithm, the canonical example being inference for model parameters after a model selection…